3D keypoint detection benchmarks under P1 setting are presented in the main paper and additional benchmarks under P2 and P3 are provided here. In Table REF , we show results on the cross-action (P2) performance of the FCN method [1]}. Compared with Protocol 1, we observe that training with fewer actions and testing on unseen actions degrade the precision significantly, especially for cross-evaluation on the whole body category which seems to have a large action distribution misalignment with the other two categories. Furthermore, deep learning models are sensitive to viewing angles [2]}, [3]}, we thus report results of cross-view (P3) in Table REF . When the model is only trained on one view (, View 0), we observe a considerable domain gap across different views as the errors increase as the deviation from the test view from the training view increases. The experiment results indicate that cross-view 3D keypoint detection is challenging.
